Wheat Bran Polymer Scaffolds: Supporting Triple-Negative Breast Cancer Cell Growth and Development
Bibliographic record
Abstract
Arabinoxylans (AX) are functional biopolymers, the main non-starch polysaccharides in cereals and other plants. AX is composed of xylose and arabinose, and the ester-linkage of ferulic acid to arabinose confers its bioactive properties. The backbone of AX resembles that of glycosaminoglycans, a major component of the human extracellular matrix. This study explores the potential of wheat bran AX-based scaffolds as a novel platform for the growth and development of triple-negative breast cancer (TNBC) cells, an aggressive form of breast cancer. Importantly, patients face the worst prognosis due to the stemness of the TNBC cells and the formation of hypoxic cell clumps. Wheat bran constitutes 15-25% of the byproducts after milling and adds limited economic value. We have extracted AX from wheat bran (WBAX) and developed soft scaffolds with Na-alginate. The scaffolds were seeded with the triple-negative breast cancer cell line MDA-MB-231. Over 21 days, cell growth and development, cell migration within the hydrogels, and the formation of hypoxic regions within cell clumps were observed. These findings suggest that WBAX-based scaffolds provide a conducive environment for TNBC cell proliferation and development, offering a promising avenue for further research into cancer cell biology and potential therapeutic applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".